Popper on instrumentalism and conventionalism

[The scientist’s] aim is to find explanatory theories (if possible, true explanatory theories); that is to say, theories which describe certain structural properties of the world, and which permit us to deduce, with the help of initial conditions, the effects to be explained.

“Initial conditions” are singular statements that apply to a specific event in question. Combining these with universal laws produces predictions. Popper doesn’t require that every event can be deductively predicted from universal laws. But science has to search for such laws that causally explain events. Popper contends that while scientific laws are not verifiable, they are falsifiable.

One angle from which the primacy of falsification might be challenged is instrumentalism. Berkeley suggested abstract theories are instruments for the prediction of observable phenomena, and not genuine assertions about the world. The difference is that between “all models are wrong” and “all models are falsifiable”.

There is no sharp dividing line between an ’empirical language’ and a ‘theoretical language’: we are theorizing all the time, even when we make the most trivial singular statement.

We are always using models, so we’re always wrong. Personally, I can live with this. Under instrumentalism, the crucial question becomes “how wrong”. As long as measurements are taken to be real features of the world, the answer to this can be used in falsificationism.

But what if measurements are dependent on assumptions? This is an implication of conventionalism. Duhem held that universal laws are merely human conventions. Since measurements depend on these laws, a conventionalist might argue that theoretical systems are not only unverifiable but also unfalsifiable. Popper makes a value judgement against conventionalism, not because it’s demonstrably wrong but because it allows explaining away, rendering it useless for science. He quotes Joseph Black:

A nice adaptation of conditions will make almost any hypothesis agree with the phenomena. This will please the imagination but does not advance our knowledge.

Statistics makes such adaptation even easier: the phenomena were merely improbable. The rise of probabilistic models makes it even more valuable to guard against ad hoc adaptations.